The positioning of the apple growth cycle plays a very important role in predicting the development of apples and guiding fruit farmers in agricultural operations. The traditional method of manually positioning the apple growth cycle has problems such as low efficiency and poor accuracy. Pattern recognition provides support for continuous and rapid positioning during the apple growth process. Under the natural conditions of the orchard, due to the large differences in the individual colors of the apples during the growth process and the influence of factors such as light changes, the photographed apple images are more complex, which brings certain difficulties to the segmentation and recognition of the apples. In this paper, pattern recognition is used to automatically identify and extract the growth stages of apples, a hue intensity (HI) color segmentation algorithm based on a Gaussian distribution model based on prior knowledge is studied, and then an active shape model (ASM) is used to identify each period of apple growth based on pattern recognition. After a series of experimental verifications, the ASM-based automatic identification method proposed in this paper is feasible and can identify the various growth periods of apples, thereby serving the mechanized production of apples.

中文翻译：

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基于模式识别的苹果成长周期定位

苹果生长周期的定位在预测苹果的生长和指导果农从事农业活动中起着非常重要的作用。传统的人工定位苹果生长周期的方法存在效率低，精度差等问题。模式识别为苹果生长过程中的连续快速定位提供了支持。在果园的自然条件下，由于苹果在生长过程中各个颜色的差异很大，并且由于光线变化等因素的影响，所拍摄的苹果图像更加复杂，给分割和分割带来一定的困难。对苹果的认可。在本文中，模式识别用于自动识别和提取苹果的生长阶段，研究了基于先验知识的基于高斯分布模型的色调强度（HI）颜色分割算法，然后使用主动形状模型（ASM）基于模式识别来识别苹果生长的每个时期。经过一系列实验验证，本文提出的基于ASM的自动识别方法是可行的，并且可以识别苹果的各个生长期，从而为苹果的机械化生产服务。